The specific energy of Li metal batteries(LMBs)can be improved by using high‐voltage cathode materials;however,achieving long‐term stable cycling performance in the corresponding system is particularly challenging f...The specific energy of Li metal batteries(LMBs)can be improved by using high‐voltage cathode materials;however,achieving long‐term stable cycling performance in the corresponding system is particularly challenging for the liquid electrolyte.Herein,a novel pseudo‐oversaturated electrolyte(POSE)is prepared by introducing 1,1,2,2‐tetrafluoroethyl‐2,2,3,3‐tetrafluoropropyl ether(TTE)to adjust the coordination structure between diglyme(G2)and lithium bis(trifluoromethanesulfonyl)imide(LiTFSI).Surprisingly,although TTE shows little solubility to LiTFSI,the molar ratio between LiTFSI and G2 in the POSE can be increased to 1:1,which is much higher than that of the saturation state,1:2.8.Simulation and experimental results prove that TTE promotes closer contact of the G2 molecular with Li^(+)in the POSE.Moreover,it also participates in the formation of electrolyte/electrode interphases.The electrolyte shows outstanding compatibility with both the Li metal anode and typical high‐voltage cathodes.Li||Li symmetric cells show a long life of more than 2000 h at 1 mA cm^(−2),1 mAh cm^(−2).In the meantime,Li||LiNi_(0.8)Co_(0.1)Mn_(0.1)O_(2)(NCM811)cell with the POSE shows a high reversible capacity of 134.8 mAh g^(−1 )after 900 cycles at 4.5 V,1 C rate.The concept of POSE can provide new insight into the Li^(+)solvation structure and in the design of advanced electrolytes for LMBs.展开更多
Soy polysaccharide(SP)has been reported to possess the properties of modulating gut microbiome diversity.Here,we aimed to explore the protective effects of SP against dextran sulphate sodium(DSS)-induced colitis.Pre-t...Soy polysaccharide(SP)has been reported to possess the properties of modulating gut microbiome diversity.Here,we aimed to explore the protective effects of SP against dextran sulphate sodium(DSS)-induced colitis.Pre-treatment with SP at a dosage of 400 mg/kg·day alleviated colitis symptoms,preventing the weight loss and colon shorten.SP suppressed DSS-induced inflammatory response and enhanced M1 to M2 macrophage polarization.Further investigation showed that SP significantly promoted the regeneration of crypt and the expansion of goblet cell production.In addition,bacterial 16S rRNA sequencing analysis showed that SP modulated the composition of fecal microbiota,including selectively increasing Lactobacillus relative abundance.Notably,SP treatment enriched the production of Lactobacillus-derived lactic acid,which was sensed by its specific G-protein-coupled receptor 81(Gpr81)/Wnt3/β-catenin signaling,and promoted the regeneration of intestinal stem cells.Fecal microbiome transplantation demonstrated that intestinal flora partially contributed to the beneficial effects of SP on preventing against colitis.In conclusion,SP exhibited the protective effects against colitis,which could be partly associated with modulating the composition of gut microbiota and enrichment of lactic acid.This study suggests that SP has potential to be developed as nutritional intervention to prevent colitis.展开更多
Land ecosystem is a unified whole formed by the interaction between natural elements and human activities in the earth surface system.With the increasingly serious eco-environmental problems,the health problems of lan...Land ecosystem is a unified whole formed by the interaction between natural elements and human activities in the earth surface system.With the increasingly serious eco-environmental problems,the health problems of land ecosystem have attracted more and more attention.In order to fully understand the development trends and achievements of land ecosystem health assessment at home and abroad,this paper reviews the literature on land ecological health assessment from four aspects:connotation,evaluation system,evaluation method and evaluation scale of land ecosystem health assessment.展开更多
Green and sustainable options are needed to ease the current energy and environmental crisis, and alleviate the greenhouse effect and energy shortage. As an alternative carbon–neutral synthetic fuel, ammonia shows gr...Green and sustainable options are needed to ease the current energy and environmental crisis, and alleviate the greenhouse effect and energy shortage. As an alternative carbon–neutral synthetic fuel, ammonia shows great potential due to its high energy density, non-toxic by-products, and mature related infrastructures. However, related practical applications have been severely hampered on ammoniaoxidation due to the high cost of catalysts and immature energy utilization systems. Here, we comprehensively summarized the efforts which have been made in recent years with the aim of providing a deep sight into the development and deficiencies in this territory and trying to establish a simple framework of basic knowledge for researchers. The exploration of mechanism is discussed first and then the relevant catalysts studied in recent years are summarized. Besides, the progress of direct ammonia fuel cells(DAFCs) is also presented and the challenges as well as perspectives on future developments of electrocatalysts for ammonia electro-oxidation and its practical application are provided at the end.展开更多
One of the fundamental driving forces in the materials science community is the hunt for new materials with specific properties that meet the requirements of rapidly evolving technology.
With the continuous expansion of software scale,software update and maintenance have become more and more important.However,frequent software code updates will make the software more likely to introduce new defects.So...With the continuous expansion of software scale,software update and maintenance have become more and more important.However,frequent software code updates will make the software more likely to introduce new defects.So how to predict the defects quickly and accurately on the software change has become an important problem for software developers.Current defect prediction methods often cannot reflect the feature information of the defect comprehensively,and the detection effect is not ideal enough.Therefore,we propose a novel defect prediction model named ITNB(Improved Transfer Naive Bayes)based on improved transfer Naive Bayesian algorithm in this paper,which mainly considers the following two aspects:(1)Considering that the edge data of the test set may affect the similarity calculation and final prediction result,we remove the edge data of the test set when calculating the data similarity between the training set and the test set;(2)Considering that each feature dimension has different effects on defect prediction,we construct the calculation formula of training data weight based on feature dimension weight and data gravity,and then calculate the prior probability and the conditional probability of training data from the weight information,so as to construct the weighted bayesian classifier for software defect prediction.To evaluate the performance of the ITNB model,we use six datasets from large open source projects,namely Bugzilla,Columba,Mozilla,JDT,Platform and PostgreSQL.We compare the ITNB model with the transfer Naive Bayesian(TNB)model.The experimental results show that our ITNB model can achieve better results than the TNB model in terms of accurary,precision and pd for within-project and cross-project defect prediction.展开更多
SaaS software that provides services through cloud platform has been more widely used nowadays.However,when SaaS software is running,it will suffer from performance fault due to factors such as the software structural...SaaS software that provides services through cloud platform has been more widely used nowadays.However,when SaaS software is running,it will suffer from performance fault due to factors such as the software structural design or complex environments.It is a major challenge that how to diagnose software quickly and accurately when the performance fault occurs.For this challenge,we propose a novel performance fault diagnosis method for SaaS software based on GBDT(Gradient Boosting Decision Tree)algorithm.In particular,we leverage the monitoring mean to obtain the performance log and warning log when the SaaS software system runs,and establish the performance fault type set and determine performance log feature.We also perform performance fault type annotation for the performance log combined with the analysis result of the warning log.Moreover,we deal with the incomplete performance log and the type non-equalization problem by using the mean filling for the same type and combination of SMOTE(Synthetic Minority Oversampling Technique)and undersampling methods.Finally,we conduct an empirical study combined with the disaster reduction system deployed on the cloud platform,and it demonstrates that the proposed method has high efficiency and accuracy for the performance diagnosis when SaaS software system runs.展开更多
Electro-oxidation of 5-hydroxymethylfurfural(HMFOR)is a promising green approach to realize the conversion of biomass into value-added chemicals.However,considering the complexity of the molecular structure of HMF,an ...Electro-oxidation of 5-hydroxymethylfurfural(HMFOR)is a promising green approach to realize the conversion of biomass into value-added chemicals.However,considering the complexity of the molecular structure of HMF,an in-depth understanding of the electrocatalytic behavior of HMFOR has rarely been investigated.Herein,the electrocatalytic mechanism of HMFOR on nickel nitride(Ni3 N)is elucidated by operando X-ray absorption spectroscopy(XAS),in situ Raman,quasi in situ X-ray photoelectron spectroscopy(XPS),and operando electrochemical impedance spectroscopy(EIS),respectively.The activity origin is proved to be Ni^(2+δ)N(OH)ads generated by the adsorbed hydroxyl group.Moreover,HMFOR on Ni3 N relates to a two-step reaction:Initially,the applied potential drives Ni atoms to lose electrons and adsorb OH-after 1.35 VRHE,giving rise to Ni^(2+δ)N(OH)ads with the electrophilic oxygen;then Ni^(2+δ)N(OH)ads seizes protons and electrons from HMF and leaves as H_(2) O spontaneously.Furthermore,the high electrolyte alkalinity favors the HMFOR process due to the increased active species(Ni^(2+δ)N(OH)ads)and the enhanced adsorption of HMF on the Ni3 N surface.This work could provide an in-depth understanding of the electrocatalytic mechanism of HMFOR on Ni3 N and demonstrate the alkalinity effect of the electrolyte on the electrocatalytic performance of HMFOR.展开更多
Software defect prediction is a research hotspot in the field of software engineering.However,due to the limitations of current machine learning algorithms,we can’t achieve good effect for defect prediction by only u...Software defect prediction is a research hotspot in the field of software engineering.However,due to the limitations of current machine learning algorithms,we can’t achieve good effect for defect prediction by only using machine learning algorithms.In previous studies,some researchers used extreme learning machine(ELM)to conduct defect prediction.However,the initial weights and biases of the ELM are determined randomly,which reduces the prediction performance of ELM.Motivated by the idea of search based software engineering,we propose a novel software defect prediction model named KAEA based on kernel principal component analysis(KPCA),adaptive genetic algorithm,extreme learning machine and Adaboost algorithm,which has three main advantages:(1)KPCA can extract optimal representative features by leveraging a nonlinear mapping function;(2)We leverage adaptive genetic algorithm to optimize the initial weights and biases of ELM,so as to improve the generalization ability and prediction capacity of ELM;(3)We use the Adaboost algorithm to integrate multiple ELM basic predictors optimized by adaptive genetic algorithm into a strong predictor,which can further improve the effect of defect prediction.To effectively evaluate the performance of KAEA,we use eleven datasets from large open source projects,and compare the KAEA with four machine learning basic classifiers,ELM and its three variants.The experimental results show that KAEA is superior to these baseline models in most cases.展开更多
Software defect prediction plays an important role in software quality assurance.However,the performance of the prediction model is susceptible to the irrelevant and redundant features.In addition,previous studies mos...Software defect prediction plays an important role in software quality assurance.However,the performance of the prediction model is susceptible to the irrelevant and redundant features.In addition,previous studies mostly regard software defect prediction as a single objective optimization problem,and multi-objective software defect prediction has not been thoroughly investigated.For the above two reasons,we propose the following solutions in this paper:(1)we leverage an advanced deep neural network-Stacked Contractive AutoEncoder(SCAE)to extract the robust deep semantic features from the original defect features,which has stronger discrimination capacity for different classes(defective or non-defective).(2)we propose a novel multi-objective defect prediction model named SMONGE that utilizes the Multi-Objective NSGAII algorithm to optimize the advanced neural network-Extreme learning machine(ELM)based on state-of-the-art Pareto optimal solutions according to the features extracted by SCAE.We mainly consider two objectives.One objective is to maximize the performance of ELM,which refers to the benefit of the SMONGE model.Another objective is to minimize the output weight norm of ELM,which is related to the cost of the SMONGE model.We compare the SCAE with six state-of-the-art feature extraction methods and compare the SMONGE model with multiple baseline models that contain four classic defect predictors and the MONGE model without SCAE across 20 open source software projects.The experimental results verify that the superiority of SCAE and SMONGE on seven evaluation metrics.展开更多
Grain size is a determinant of rice grain yield.In plants,mitochondria supply energy for cellular metabolism via the mitochondrial electron transport chain.Here we report that OsNDB2,which encodes a putative rotenone-...Grain size is a determinant of rice grain yield.In plants,mitochondria supply energy for cellular metabolism via the mitochondrial electron transport chain.Here we report that OsNDB2,which encodes a putative rotenone-insensitive typeⅡNAD(P)H dehydrogenase(ND),negatively regulates grain size and weight in rice.Six ND members representing three major types of rice were identified,and the predicted OsNDB2 protein was localized to mitochondria.Contents of OsNDB2 transcripts were higher in young panicles and leaf blades.OsNDB2 overexpression reduced grain length,grain width,and 1000-grain weight and moderately influenced plant height,while knockout of OsNDB2 increased grain size and 1000-grain weight.Allelic mutations of OsNDB2 were associated with diverse grain appearances.Cellular observations revealed that variations in grain size of transgenic lines were caused by change in cell expansion but not cell proliferation in spikelet hulls.Our study sheds light on OsNDB2 function and provides a new potential breeding approach for increasing rice grain size and weight.展开更多
In this letter, the physical layer security of hybrid automatic repeat request with chase combining(HARQ-CC) scheme is investigated from the viewpoint of information theory. Different from the literature which used Wy...In this letter, the physical layer security of hybrid automatic repeat request with chase combining(HARQ-CC) scheme is investigated from the viewpoint of information theory. Different from the literature which used Wyner code, our analysis focuses on the general scenario without specific code. We firstly obtain the outage probability of both main channel and wiretap channel. Since retransmissions are completely determined by main channel, we then prove that its achievable diversity order equals to maximum transmission number() while this order of wiretap channel is only one. Furthermore, we evaluate the metric of secure gap which demonstrates the difference between main channel and wiretap channel with reliable and secure constraints. As increases, the secure gap decreases monotonously. When is large enough, the security can be guaranteed even if wiretap channel is better than main channel.展开更多
Electronic regulation of carbon is essential for developing non-platinum electrocatalysts for oxygen reduction reactions(ORRs).In this work,we used Cs to further regulate the electronic structure of nitrogen-doped(N-d...Electronic regulation of carbon is essential for developing non-platinum electrocatalysts for oxygen reduction reactions(ORRs).In this work,we used Cs to further regulate the electronic structure of nitrogen-doped(N-doped)carbon.The Cs atoms coordinated with the nitrogen atom in the N-doped carbon for injecting electrons into the carbon conjugate structure and reducing the work function of the carbon network.The low-work-function surface improved electron donation,facilitated O_(2) dissociation,and enhanced the adsorption of an OOH^(*) intermediate.Thus,electrocatalytic performance for the ORR was improved.The material shows potential as an ORR electrocatalyst comparable with Pt/C.展开更多
Software defect prediction plays a very important role in software quality assurance,which aims to inspect as many potentially defect-prone software modules as possible.However,the performance of the prediction model ...Software defect prediction plays a very important role in software quality assurance,which aims to inspect as many potentially defect-prone software modules as possible.However,the performance of the prediction model is susceptible to high dimensionality of the dataset that contains irrelevant and redundant features.In addition,software metrics for software defect prediction are almost entirely traditional features compared to the deep semantic feature representation from deep learning techniques.To address these two issues,we propose the following two solutions in this paper:(1)We leverage a novel non-linear manifold learning method-SOINN Landmark Isomap(SL-Isomap)to extract the representative features by selecting automatically the reasonable number and position of landmarks,which can reveal the complex intrinsic structure hidden behind the defect data.(2)We propose a novel defect prediction model named DLDD based on hybrid deep learning techniques,which leverages denoising autoencoder to learn true input features that are not contaminated by noise,and utilizes deep neural network to learn the abstract deep semantic features.We combine the squared error loss function of denoising autoencoder with the cross entropy loss function of deep neural network to achieve the best prediction performance by adjusting a hyperparameter.We compare the SL-Isomap with seven state-of-the-art feature extraction methods and compare the DLDD model with six baseline models across 20 open source software projects.The experimental results verify that the superiority of SL-Isomap and DLDD on four evaluation indicators.展开更多
Myocardial perfusion imaging(MPI) is valuable for the diagnosis,prognosis,and management of coronary artery disease(CAD).The most commonly used pharmacologic stress agents at present are vasodilators and adrenergic ag...Myocardial perfusion imaging(MPI) is valuable for the diagnosis,prognosis,and management of coronary artery disease(CAD).The most commonly used pharmacologic stress agents at present are vasodilators and adrenergic agents.However,these agents have contraindications and may cause adverse effects in some patients.Thus,other stress agents feasible for more patients are required.Higenamine(HG) is a β-adrenergic receptor agonist currently approved for clinical trials as a stress agent for myocardial infarction.It also has a promising value in MPI for the detection of CAD in preclinical and clinical studies.This review summarizes the application of HG on MPI,including its mechanism of action,stress protocol,efficacy,and safety.展开更多
Transparent solar-blind ultraviolet photodetectors(SBUV PDs)have extensive applications in versatile scenarios,such as optical communication.However,it is still challenging to simultaneously achieve high responsivity,...Transparent solar-blind ultraviolet photodetectors(SBUV PDs)have extensive applications in versatile scenarios,such as optical communication.However,it is still challenging to simultaneously achieve high responsivity,high transparency,and satisfying self-powered capability.Here,we demonstrated high-performance,transparent,and self-powered photoelectrochemical-type(PEC)SBUV PDs based on vertically grown ultrathin In_(2)O_(3) nanosheet arrays(NAs)with a three-dimensional(3D)porous structure.The 3D porous structure simultaneously improves the transmittance in the visible light region,accelerates interfacial reaction kinetics,and promotes photogenerated carrier transport.The performance of In_(2)O_(3) NAs photoanodes exceeds most reported self-powered PEC SBUV PDs,exhibiting a high transmittance of approximately 80%in the visible light region,a high responsivity of 86.15 mA/W for 254 nm light irradiation,a fast response speed of 15/18 ms,and good multicycle stability.The In_(2)O_(3) NAs also show excellent spectral selectivity with an ultrahigh solar-blind rejection ratio of 1319.30,attributed to the quantum confinement effect induced by the ultrathin feature(2-3 nm).Furthermore,In_(2)O_(3) NAs photoanodes show good capability in underwater optical communication.Our work demonstrated that a 3D porous structure is a powerful strategy to synchronously achieve high responsivity and transparency and provides a new perspective for designing high-performance,transparent,and self-powered PEC SBUV PDs.展开更多
One of the bottlenecks limiting the cycling stability of high voltage lithium metal batteries(LMBs)is the lack of suitable electrolytes.Herein,phenyl vinyl sulfone(PVS)is proposed as a multifunctional additive to stab...One of the bottlenecks limiting the cycling stability of high voltage lithium metal batteries(LMBs)is the lack of suitable electrolytes.Herein,phenyl vinyl sulfone(PVS)is proposed as a multifunctional additive to stabilize both cathode and anode interfaces as it can be preferentially oxidized/reduced on the electrode surfaces.The PVS derived solid electrolyte interphase films can not only reduce the transition metal dissolution on the cathode side,but also suppress the Li dendrite spread on the lithium anode side.The Li||Li symmetric battery with PVS addition delivers longer cycle life and a higher critical current density of over 3.0 m Ah cm^(-2).The LiNi_(0.8)Co_(0.1)Mn0.1O_(2)(NCM811)||Li full cell exhibits excellent capacity retention of 80.8%or 80.0%after 400 cycles at 0.5 C or 1 C rate with the voltage range of 3.0–4.3 V.In particular,the NCM811||Li cell under constrained conditions remains operation over 150 cycles.This work offers new insights into the electrolyte formulations for the next generation of LMBs.展开更多
Pt/CeO2 catalysts with unitary Pt species,nanoparticles,clusters or single atoms,often exhibit excellent activity and unique selectivity in many catalytic reactions benefiting from their small size,abundant unsaturate...Pt/CeO2 catalysts with unitary Pt species,nanoparticles,clusters or single atoms,often exhibit excellent activity and unique selectivity in many catalytic reactions benefiting from their small size,abundant unsaturated active sites,and unique electro nic structure.In recent years,a tre mendous number of related articles have provided great inspiration to future research and development of Pt/CeO2 catalysts.In this review,the state-of-the-art evolution of Pt nanoparticles to Pt single atoms on CeO2 is reviewed with the emphasis on synthetic strategies,advanced characterization techniques(allowing one to clarify the single atoms from clusters),the catalytic applications and mechanisms from the viewpoint of theoretical calculation.Finally,the critical outlooks and the challenges faced in developing the single-atom Pt/CeO2 catalysts are highlighted.展开更多
Graphene is a two-dimensional nanomaterial with huge surface area,high carrier mobility and high mechanical strength.Because of its great potential in nanotechnology and environmental protection,it has attracted much ...Graphene is a two-dimensional nanomaterial with huge surface area,high carrier mobility and high mechanical strength.Because of its great potential in nanotechnology and environmental protection,it has attracted much attention in environmental and energy fields since its discovery in 2004.Although graphene is a star material,many reviews have introduced its use in terms of energy,the research progress in the field of environment,especially water pollution control,has been rarely reported.Here,we review exhaustively the research progress of graphene-based materials in environmental pollution remediation in the past ten years.Firstly,the advantages and classification of graphene were introduced.Secondly,the research progress and main achievements of graphene and its composites in the fields of photocatalytic degradation,pollutant adsorption and water treatment were emphatically described,and the mechanism of action in the above fields was summarized.Finally,we discuss the problems existing in the preparation and summarize the application of graphene in the environment.展开更多
基金Subsidy for Hebei Key Laboratory of Applied Chemistry after Operation Performance,Grant/Award Number:22567616HNatural Science Foundation of Hebei Province of China,Grant/Award Number:B2020103028+3 种基金Science Fund for Creative Research Groups of the National Natural Science Foundation of China,Grant/Award Number:21921005National Key Research and Development Program of China,Grant/Award Number:2021YFB2400300Beijing Municipal Natural Science Foundation Project,Grant/Award Number:2222031National Natural Science Foundation of China,Grant/Award Numbers:52174281,21808228。
文摘The specific energy of Li metal batteries(LMBs)can be improved by using high‐voltage cathode materials;however,achieving long‐term stable cycling performance in the corresponding system is particularly challenging for the liquid electrolyte.Herein,a novel pseudo‐oversaturated electrolyte(POSE)is prepared by introducing 1,1,2,2‐tetrafluoroethyl‐2,2,3,3‐tetrafluoropropyl ether(TTE)to adjust the coordination structure between diglyme(G2)and lithium bis(trifluoromethanesulfonyl)imide(LiTFSI).Surprisingly,although TTE shows little solubility to LiTFSI,the molar ratio between LiTFSI and G2 in the POSE can be increased to 1:1,which is much higher than that of the saturation state,1:2.8.Simulation and experimental results prove that TTE promotes closer contact of the G2 molecular with Li^(+)in the POSE.Moreover,it also participates in the formation of electrolyte/electrode interphases.The electrolyte shows outstanding compatibility with both the Li metal anode and typical high‐voltage cathodes.Li||Li symmetric cells show a long life of more than 2000 h at 1 mA cm^(−2),1 mAh cm^(−2).In the meantime,Li||LiNi_(0.8)Co_(0.1)Mn_(0.1)O_(2)(NCM811)cell with the POSE shows a high reversible capacity of 134.8 mAh g^(−1 )after 900 cycles at 4.5 V,1 C rate.The concept of POSE can provide new insight into the Li^(+)solvation structure and in the design of advanced electrolytes for LMBs.
基金funded by National Natural Science Foundation of China(NSFC32372350)the Knowledge Innovation Program Funding of Institute of Food Science and Technology(CAASASTIP2021-IFST)+1 种基金China Agriculture Research System(CARS-04)Agricultural Science and Technology Innovation Program of Institute of Food Science and Technology,Chinese Academy of Agricultural Sciences(CAAS-ASTIP-G2022-IFST-06).
文摘Soy polysaccharide(SP)has been reported to possess the properties of modulating gut microbiome diversity.Here,we aimed to explore the protective effects of SP against dextran sulphate sodium(DSS)-induced colitis.Pre-treatment with SP at a dosage of 400 mg/kg·day alleviated colitis symptoms,preventing the weight loss and colon shorten.SP suppressed DSS-induced inflammatory response and enhanced M1 to M2 macrophage polarization.Further investigation showed that SP significantly promoted the regeneration of crypt and the expansion of goblet cell production.In addition,bacterial 16S rRNA sequencing analysis showed that SP modulated the composition of fecal microbiota,including selectively increasing Lactobacillus relative abundance.Notably,SP treatment enriched the production of Lactobacillus-derived lactic acid,which was sensed by its specific G-protein-coupled receptor 81(Gpr81)/Wnt3/β-catenin signaling,and promoted the regeneration of intestinal stem cells.Fecal microbiome transplantation demonstrated that intestinal flora partially contributed to the beneficial effects of SP on preventing against colitis.In conclusion,SP exhibited the protective effects against colitis,which could be partly associated with modulating the composition of gut microbiota and enrichment of lactic acid.This study suggests that SP has potential to be developed as nutritional intervention to prevent colitis.
文摘Land ecosystem is a unified whole formed by the interaction between natural elements and human activities in the earth surface system.With the increasingly serious eco-environmental problems,the health problems of land ecosystem have attracted more and more attention.In order to fully understand the development trends and achievements of land ecosystem health assessment at home and abroad,this paper reviews the literature on land ecological health assessment from four aspects:connotation,evaluation system,evaluation method and evaluation scale of land ecosystem health assessment.
基金supported by the National Natural Science Foundation of China (Grant Nos. 21905088, 21902047, 21573066, 21825201, 2187350, and 51402100)the Provincial Natural Science Foundation of Hunan (2020JJ5045)。
文摘Green and sustainable options are needed to ease the current energy and environmental crisis, and alleviate the greenhouse effect and energy shortage. As an alternative carbon–neutral synthetic fuel, ammonia shows great potential due to its high energy density, non-toxic by-products, and mature related infrastructures. However, related practical applications have been severely hampered on ammoniaoxidation due to the high cost of catalysts and immature energy utilization systems. Here, we comprehensively summarized the efforts which have been made in recent years with the aim of providing a deep sight into the development and deficiencies in this territory and trying to establish a simple framework of basic knowledge for researchers. The exploration of mechanism is discussed first and then the relevant catalysts studied in recent years are summarized. Besides, the progress of direct ammonia fuel cells(DAFCs) is also presented and the challenges as well as perspectives on future developments of electrocatalysts for ammonia electro-oxidation and its practical application are provided at the end.
基金supported by the National Natural Science Foundation of China(Grant Nos.21701043,21825201 and U19A2017)the Provincial Natural Science Foundation of Hunan(2019GK2031)+1 种基金the Open Project Program of Key Laboratory of Low Dimensional Materials&Application Technology(Xiangtan University),Ministry of Education,China(No.KF20180202)the China Postdoctoral Science Foundation(Grant Nos.2019 M662766,2019 M662759,2020 M682549,and 2020 M672473)。
文摘One of the fundamental driving forces in the materials science community is the hunt for new materials with specific properties that meet the requirements of rapidly evolving technology.
基金This work is supported in part by the National Science Foundation of China(Nos.61672392,61373038)in part by the National Key Research and Development Program of China(No.2016YFC1202204).
文摘With the continuous expansion of software scale,software update and maintenance have become more and more important.However,frequent software code updates will make the software more likely to introduce new defects.So how to predict the defects quickly and accurately on the software change has become an important problem for software developers.Current defect prediction methods often cannot reflect the feature information of the defect comprehensively,and the detection effect is not ideal enough.Therefore,we propose a novel defect prediction model named ITNB(Improved Transfer Naive Bayes)based on improved transfer Naive Bayesian algorithm in this paper,which mainly considers the following two aspects:(1)Considering that the edge data of the test set may affect the similarity calculation and final prediction result,we remove the edge data of the test set when calculating the data similarity between the training set and the test set;(2)Considering that each feature dimension has different effects on defect prediction,we construct the calculation formula of training data weight based on feature dimension weight and data gravity,and then calculate the prior probability and the conditional probability of training data from the weight information,so as to construct the weighted bayesian classifier for software defect prediction.To evaluate the performance of the ITNB model,we use six datasets from large open source projects,namely Bugzilla,Columba,Mozilla,JDT,Platform and PostgreSQL.We compare the ITNB model with the transfer Naive Bayesian(TNB)model.The experimental results show that our ITNB model can achieve better results than the TNB model in terms of accurary,precision and pd for within-project and cross-project defect prediction.
基金This work is supported in part by the National Science Foundation of China(61672392,61373038)in part by the National Key Research and Development Program of China(No.2016YFC1202204).
文摘SaaS software that provides services through cloud platform has been more widely used nowadays.However,when SaaS software is running,it will suffer from performance fault due to factors such as the software structural design or complex environments.It is a major challenge that how to diagnose software quickly and accurately when the performance fault occurs.For this challenge,we propose a novel performance fault diagnosis method for SaaS software based on GBDT(Gradient Boosting Decision Tree)algorithm.In particular,we leverage the monitoring mean to obtain the performance log and warning log when the SaaS software system runs,and establish the performance fault type set and determine performance log feature.We also perform performance fault type annotation for the performance log combined with the analysis result of the warning log.Moreover,we deal with the incomplete performance log and the type non-equalization problem by using the mean filling for the same type and combination of SMOTE(Synthetic Minority Oversampling Technique)and undersampling methods.Finally,we conduct an empirical study combined with the disaster reduction system deployed on the cloud platform,and it demonstrates that the proposed method has high efficiency and accuracy for the performance diagnosis when SaaS software system runs.
基金supported by the National Key R&D Program of China(2020YFA0710000)the National Natural Science Foundation of China(Grant No.:21902047)+1 种基金the Provincial Natural Science Foundation of Hunan(2020JJ5045)the Fundamental Research Funds for the Central Universities(Grant No.531118010127)。
文摘Electro-oxidation of 5-hydroxymethylfurfural(HMFOR)is a promising green approach to realize the conversion of biomass into value-added chemicals.However,considering the complexity of the molecular structure of HMF,an in-depth understanding of the electrocatalytic behavior of HMFOR has rarely been investigated.Herein,the electrocatalytic mechanism of HMFOR on nickel nitride(Ni3 N)is elucidated by operando X-ray absorption spectroscopy(XAS),in situ Raman,quasi in situ X-ray photoelectron spectroscopy(XPS),and operando electrochemical impedance spectroscopy(EIS),respectively.The activity origin is proved to be Ni^(2+δ)N(OH)ads generated by the adsorbed hydroxyl group.Moreover,HMFOR on Ni3 N relates to a two-step reaction:Initially,the applied potential drives Ni atoms to lose electrons and adsorb OH-after 1.35 VRHE,giving rise to Ni^(2+δ)N(OH)ads with the electrophilic oxygen;then Ni^(2+δ)N(OH)ads seizes protons and electrons from HMF and leaves as H_(2) O spontaneously.Furthermore,the high electrolyte alkalinity favors the HMFOR process due to the increased active species(Ni^(2+δ)N(OH)ads)and the enhanced adsorption of HMF on the Ni3 N surface.This work could provide an in-depth understanding of the electrocatalytic mechanism of HMFOR on Ni3 N and demonstrate the alkalinity effect of the electrolyte on the electrocatalytic performance of HMFOR.
基金This work is supported in part by the National Science Foundation of China(61672392,61373038)in part by the National Key Research and Development Program of China(No.2016YFC1202204).
文摘Software defect prediction is a research hotspot in the field of software engineering.However,due to the limitations of current machine learning algorithms,we can’t achieve good effect for defect prediction by only using machine learning algorithms.In previous studies,some researchers used extreme learning machine(ELM)to conduct defect prediction.However,the initial weights and biases of the ELM are determined randomly,which reduces the prediction performance of ELM.Motivated by the idea of search based software engineering,we propose a novel software defect prediction model named KAEA based on kernel principal component analysis(KPCA),adaptive genetic algorithm,extreme learning machine and Adaboost algorithm,which has three main advantages:(1)KPCA can extract optimal representative features by leveraging a nonlinear mapping function;(2)We leverage adaptive genetic algorithm to optimize the initial weights and biases of ELM,so as to improve the generalization ability and prediction capacity of ELM;(3)We use the Adaboost algorithm to integrate multiple ELM basic predictors optimized by adaptive genetic algorithm into a strong predictor,which can further improve the effect of defect prediction.To effectively evaluate the performance of KAEA,we use eleven datasets from large open source projects,and compare the KAEA with four machine learning basic classifiers,ELM and its three variants.The experimental results show that KAEA is superior to these baseline models in most cases.
基金This work is supported in part by the National Science Foundation of China(Grant Nos.61672392,61373038)in part by the National Key Research and Development Program of China(Grant No.2016YFC1202204).
文摘Software defect prediction plays an important role in software quality assurance.However,the performance of the prediction model is susceptible to the irrelevant and redundant features.In addition,previous studies mostly regard software defect prediction as a single objective optimization problem,and multi-objective software defect prediction has not been thoroughly investigated.For the above two reasons,we propose the following solutions in this paper:(1)we leverage an advanced deep neural network-Stacked Contractive AutoEncoder(SCAE)to extract the robust deep semantic features from the original defect features,which has stronger discrimination capacity for different classes(defective or non-defective).(2)we propose a novel multi-objective defect prediction model named SMONGE that utilizes the Multi-Objective NSGAII algorithm to optimize the advanced neural network-Extreme learning machine(ELM)based on state-of-the-art Pareto optimal solutions according to the features extracted by SCAE.We mainly consider two objectives.One objective is to maximize the performance of ELM,which refers to the benefit of the SMONGE model.Another objective is to minimize the output weight norm of ELM,which is related to the cost of the SMONGE model.We compare the SCAE with six state-of-the-art feature extraction methods and compare the SMONGE model with multiple baseline models that contain four classic defect predictors and the MONGE model without SCAE across 20 open source software projects.The experimental results verify that the superiority of SCAE and SMONGE on seven evaluation metrics.
基金supported by Luoyang Key Science and Technology Innovation Program(2101016A)。
文摘Grain size is a determinant of rice grain yield.In plants,mitochondria supply energy for cellular metabolism via the mitochondrial electron transport chain.Here we report that OsNDB2,which encodes a putative rotenone-insensitive typeⅡNAD(P)H dehydrogenase(ND),negatively regulates grain size and weight in rice.Six ND members representing three major types of rice were identified,and the predicted OsNDB2 protein was localized to mitochondria.Contents of OsNDB2 transcripts were higher in young panicles and leaf blades.OsNDB2 overexpression reduced grain length,grain width,and 1000-grain weight and moderately influenced plant height,while knockout of OsNDB2 increased grain size and 1000-grain weight.Allelic mutations of OsNDB2 were associated with diverse grain appearances.Cellular observations revealed that variations in grain size of transgenic lines were caused by change in cell expansion but not cell proliferation in spikelet hulls.Our study sheds light on OsNDB2 function and provides a new potential breeding approach for increasing rice grain size and weight.
基金supported in part by the National Natural Science Foundation of China under Grant No. 61072059
文摘In this letter, the physical layer security of hybrid automatic repeat request with chase combining(HARQ-CC) scheme is investigated from the viewpoint of information theory. Different from the literature which used Wyner code, our analysis focuses on the general scenario without specific code. We firstly obtain the outage probability of both main channel and wiretap channel. Since retransmissions are completely determined by main channel, we then prove that its achievable diversity order equals to maximum transmission number() while this order of wiretap channel is only one. Furthermore, we evaluate the metric of secure gap which demonstrates the difference between main channel and wiretap channel with reliable and secure constraints. As increases, the secure gap decreases monotonously. When is large enough, the security can be guaranteed even if wiretap channel is better than main channel.
文摘Electronic regulation of carbon is essential for developing non-platinum electrocatalysts for oxygen reduction reactions(ORRs).In this work,we used Cs to further regulate the electronic structure of nitrogen-doped(N-doped)carbon.The Cs atoms coordinated with the nitrogen atom in the N-doped carbon for injecting electrons into the carbon conjugate structure and reducing the work function of the carbon network.The low-work-function surface improved electron donation,facilitated O_(2) dissociation,and enhanced the adsorption of an OOH^(*) intermediate.Thus,electrocatalytic performance for the ORR was improved.The material shows potential as an ORR electrocatalyst comparable with Pt/C.
基金This work is supported in part by the National Science Foundation of China(Grant Nos.61672392,61373038)in part by the National Key Research and Development Program of China(Grant No.2016YFC1202204).
文摘Software defect prediction plays a very important role in software quality assurance,which aims to inspect as many potentially defect-prone software modules as possible.However,the performance of the prediction model is susceptible to high dimensionality of the dataset that contains irrelevant and redundant features.In addition,software metrics for software defect prediction are almost entirely traditional features compared to the deep semantic feature representation from deep learning techniques.To address these two issues,we propose the following two solutions in this paper:(1)We leverage a novel non-linear manifold learning method-SOINN Landmark Isomap(SL-Isomap)to extract the representative features by selecting automatically the reasonable number and position of landmarks,which can reveal the complex intrinsic structure hidden behind the defect data.(2)We propose a novel defect prediction model named DLDD based on hybrid deep learning techniques,which leverages denoising autoencoder to learn true input features that are not contaminated by noise,and utilizes deep neural network to learn the abstract deep semantic features.We combine the squared error loss function of denoising autoencoder with the cross entropy loss function of deep neural network to achieve the best prediction performance by adjusting a hyperparameter.We compare the SL-Isomap with seven state-of-the-art feature extraction methods and compare the DLDD model with six baseline models across 20 open source software projects.The experimental results verify that the superiority of SL-Isomap and DLDD on four evaluation indicators.
文摘Myocardial perfusion imaging(MPI) is valuable for the diagnosis,prognosis,and management of coronary artery disease(CAD).The most commonly used pharmacologic stress agents at present are vasodilators and adrenergic agents.However,these agents have contraindications and may cause adverse effects in some patients.Thus,other stress agents feasible for more patients are required.Higenamine(HG) is a β-adrenergic receptor agonist currently approved for clinical trials as a stress agent for myocardial infarction.It also has a promising value in MPI for the detection of CAD in preclinical and clinical studies.This review summarizes the application of HG on MPI,including its mechanism of action,stress protocol,efficacy,and safety.
基金support from Fundamental Research Funds for the Central Universities(No.2572023AW26)the Innovation Foundation for the Doctoral Program of Forestry Engineering of Northeast Forestry University(No.LYGC202227).
文摘Transparent solar-blind ultraviolet photodetectors(SBUV PDs)have extensive applications in versatile scenarios,such as optical communication.However,it is still challenging to simultaneously achieve high responsivity,high transparency,and satisfying self-powered capability.Here,we demonstrated high-performance,transparent,and self-powered photoelectrochemical-type(PEC)SBUV PDs based on vertically grown ultrathin In_(2)O_(3) nanosheet arrays(NAs)with a three-dimensional(3D)porous structure.The 3D porous structure simultaneously improves the transmittance in the visible light region,accelerates interfacial reaction kinetics,and promotes photogenerated carrier transport.The performance of In_(2)O_(3) NAs photoanodes exceeds most reported self-powered PEC SBUV PDs,exhibiting a high transmittance of approximately 80%in the visible light region,a high responsivity of 86.15 mA/W for 254 nm light irradiation,a fast response speed of 15/18 ms,and good multicycle stability.The In_(2)O_(3) NAs also show excellent spectral selectivity with an ultrahigh solar-blind rejection ratio of 1319.30,attributed to the quantum confinement effect induced by the ultrathin feature(2-3 nm).Furthermore,In_(2)O_(3) NAs photoanodes show good capability in underwater optical communication.Our work demonstrated that a 3D porous structure is a powerful strategy to synchronously achieve high responsivity and transparency and provides a new perspective for designing high-performance,transparent,and self-powered PEC SBUV PDs.
基金financially supported by the National Key Research and Development Program of China(No.2019YFA0705603)Science Fund for Creative Research Groups of the National Natural Science Foundation of China(No.21921005)。
文摘One of the bottlenecks limiting the cycling stability of high voltage lithium metal batteries(LMBs)is the lack of suitable electrolytes.Herein,phenyl vinyl sulfone(PVS)is proposed as a multifunctional additive to stabilize both cathode and anode interfaces as it can be preferentially oxidized/reduced on the electrode surfaces.The PVS derived solid electrolyte interphase films can not only reduce the transition metal dissolution on the cathode side,but also suppress the Li dendrite spread on the lithium anode side.The Li||Li symmetric battery with PVS addition delivers longer cycle life and a higher critical current density of over 3.0 m Ah cm^(-2).The LiNi_(0.8)Co_(0.1)Mn0.1O_(2)(NCM811)||Li full cell exhibits excellent capacity retention of 80.8%or 80.0%after 400 cycles at 0.5 C or 1 C rate with the voltage range of 3.0–4.3 V.In particular,the NCM811||Li cell under constrained conditions remains operation over 150 cycles.This work offers new insights into the electrolyte formulations for the next generation of LMBs.
基金Project supported by the National Natural Science Foundation of China(21906063,21876061,21805112)Key Technology R&D Program of Shandong Province(2019GSF109042)。
文摘Pt/CeO2 catalysts with unitary Pt species,nanoparticles,clusters or single atoms,often exhibit excellent activity and unique selectivity in many catalytic reactions benefiting from their small size,abundant unsaturated active sites,and unique electro nic structure.In recent years,a tre mendous number of related articles have provided great inspiration to future research and development of Pt/CeO2 catalysts.In this review,the state-of-the-art evolution of Pt nanoparticles to Pt single atoms on CeO2 is reviewed with the emphasis on synthetic strategies,advanced characterization techniques(allowing one to clarify the single atoms from clusters),the catalytic applications and mechanisms from the viewpoint of theoretical calculation.Finally,the critical outlooks and the challenges faced in developing the single-atom Pt/CeO2 catalysts are highlighted.
基金supported by the State Key Research Development Program of China(No.2016YFA0204200)National Natural Science Foundation of China(Nos.21822603,21811540394,5171101651,21677048,21773062,21577036)+1 种基金Shanghai Pujiang Program(No.17PJD011)the Fundamental Research Funds for the Central Universities(No.22A201514021)。
文摘Graphene is a two-dimensional nanomaterial with huge surface area,high carrier mobility and high mechanical strength.Because of its great potential in nanotechnology and environmental protection,it has attracted much attention in environmental and energy fields since its discovery in 2004.Although graphene is a star material,many reviews have introduced its use in terms of energy,the research progress in the field of environment,especially water pollution control,has been rarely reported.Here,we review exhaustively the research progress of graphene-based materials in environmental pollution remediation in the past ten years.Firstly,the advantages and classification of graphene were introduced.Secondly,the research progress and main achievements of graphene and its composites in the fields of photocatalytic degradation,pollutant adsorption and water treatment were emphatically described,and the mechanism of action in the above fields was summarized.Finally,we discuss the problems existing in the preparation and summarize the application of graphene in the environment.
